Triple

T1564068
Position Surface form Disambiguated ID Type / Status
Subject Southeastern Colorado E33392 entity
Predicate includesCity P3207 FINISHED
Object Lamar, Colorado E112096 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lamar, Colorado | Statement: [Southeastern Colorado, includesCity, Lamar, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lamar, Colorado
Context triple: [Southeastern Colorado, includesCity, Lamar, Colorado]
  • A. Lamar, Colorado chosen
    Lamar, Colorado is a small city in southeastern Colorado known as an agricultural and transportation hub on the High Plains.
  • B. Alamosa, Colorado
    Alamosa, Colorado is a small city in the San Luis Valley known as a regional hub for southern Colorado and a gateway to Great Sand Dunes National Park.
  • C. Blende, Colorado
    Blende, Colorado is a small unincorporated community and census-designated place located near the city of Pueblo in southern Colorado.
  • D. Belmont, Colorado
    Belmont, Colorado is a residential neighborhood and former unincorporated community that is now part of the city of Pueblo in Pueblo County.
  • E. Monte Vista, Colorado
    Monte Vista, Colorado is a small city in the San Luis Valley known for its agricultural heritage and as a gateway to outdoor recreation in southern Colorado.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9089c7b9881909e44fee8053ac189 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac0be308190a12ba8e79589dead completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:27 p.m.